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Plan First

Community
goatstarter
plan-first

Explore-then-plan protocol for complex work. Use before implementing anything that spans multiple files, changes architecture, touches shared interfaces, or has ambiguous requirements. Produces a reviewable plan with acceptance criteria before any code is written. Also invoked manually via /plan-first.

Overview

Publishergoatstarter
Repositorygoat-fable
Skill nameplan-first
Stars
62
Forks
8
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by goatstarter on GitHub. Read the source before you install it.

Installation

Install the Plan First AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/goatstarter/goat-fable/tree/main/skills/plan-first
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/goatstarter/goat-fable.git /tmp/goat-fable
mkdir -p .claude/skills
cp -r /tmp/goat-fable/skills/plan-first .claude/skills/plan-first
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Plan First in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Plan First on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Plan First is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Plan First

You are about to do work that is expensive to redo. The point of this protocol: discover the surprises during exploration, when they cost minutes, not during implementation, when they cost the session. Do not write or edit any production code until step 4.

1. Explore

Read the code the task will touch, and its neighbors:

  • The files you expect to change, plus 2-3 sibling files of the same kind (to absorb the local conventions you must match).
  • The callers/consumers of anything whose interface might change (grep for them; don't rely on memory).
  • The existing tests for the area: they encode the behavioral contract, and they tell you how your change will be verified.
  • Any prior art in the repo: a similar feature already implemented is your best spec.

Broad "where does X happen?" questions: delegate to a search subagent and keep the conclusions.

2. Draft the plan

Write it down (todo list, plan file, or plan mode: whatever the session offers). It must contain:

  • Goal in one sentence, in your own words. If you can't write this sentence, you don't understand the task yet.
  • Acceptance criteria: numbered, each independently checkable. These are what "done" will be measured against, so write them as checks you can actually run.
  • File-level changes: which files change and roughly how; which files are explicitly NOT touched.
  • Sequence: what order, and where the verification checkpoints are (after which steps do the tests run?).
  • Risks and unknowns: the parts you're least sure about, and how you'll de-risk each (usually: verify the assumption first, cheaply).

3. Surface open questions, once

Collect every requirement ambiguity that materially changes the work, and ask them together in one round, each with your recommended default. One consolidated round of questions is respect for the human's time; a drip of questions across an hour is not. Minor choices don't go here: pick reasonably and note it in the plan.

If the human is unavailable and the ambiguity is non-destructive either way: state your chosen assumption prominently in the plan and proceed.

4. Execute against the plan

  • One plan item at a time to verified-done; run the checkpoint verifications as scheduled, not batched at the end.
  • Reality will disagree with the plan somewhere. When it does, update the written plan and say so; don't silently diverge. If the divergence changes scope or acceptance criteria, that's a question, not a judgment call.
  • Finish with the acceptance criteria as your checklist: demonstrate each one.

Frequently asked questions

What does the Plan First AI skill do?

Explore-then-plan protocol for complex work. Use before implementing anything that spans multiple files, changes architecture, touches shared interfaces, or has ambiguous requirements. Produces a reviewable plan with acceptance criteria before any code is written. Also invoked manually via /plan-first.

Why use Plan First on TypingMind?

Because you install it once and use it with any model. Plan First is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Plan First in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/goatstarter/goat-fable/tree/main/skills/plan-first. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Plan First?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Plan First?

As many as you like. As long as a model supports skills, you can use Plan First with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Plan First AI skill free?

Yes. It is published on GitHub by goatstarter under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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